Managing collaborative feedback information for distributed retrieval

Authors:
Pascal Felber;Toan Luu;Martin Rajman;Etienne Riviere
Affiliations:
Université de Neuchâtel, Neuchâtel, Switzerland;Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland;Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland;Université de Neuchâtel, Neuchâtel, Switzerland
Venue:
Proceedings of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval
Year:
2008

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Abstract

Despite the many research efforts invested recently in peer-to-peer search engines, none of the proposed system has reached the level of quality and efficiency of their centralized counterpart. One of the main reasons for this inferior performance is the difficulty to attract a critical mass of users that would make the peer-to-peer system truly competitive. We argue that decentralized search mechanisms should not aim at replacing existing engines, but instead complement them by adding novel functionalities that would be difficult to provide in a centralized manner. This paper introduces an example of such a complementary search mechanism and presents the design of a distributed collaborative system for leveraging user feedback and document/user profiling information.